Since everybody speaks about the wonders of AI (at least it feels like that), it is prudent to remind people that you still need to understand what you are doing and where you want to deploy it. And we are happy to have found an expert in this topic.
Bassam AlKharashi is a Saudi entrepreneur, business transformation leader, and AI strategist with more than 30 years of experience across technology, BPM, enterprise architecture, innovation, and entrepreneurship.
His background in process management has been a constant foundation: he has helped develop the process-management profession in the region and authored and co-authored books on process management and innovation. His interest in AI goes back to his graduate studies in computer engineering at Case Western Reserve University in the early 1990s, where his work included neural networks.
Today, Bassam is the Founder and CEO of Nuhaa AI, helping organizations move from isolated AI experiments toward governed, production-grade AI transformation. His current work explores how AI changes business processes, enterprise architecture, and organizational design and how BPM can evolve as organizations become AI-native.
In this episode of the podcast, we talk about:
— AI as a Driver for Growth, Not Just Speed: Use AI to unlock new capabilities and market growth, not merely as a faster replacement for rule-based automation.
— AI Agents are Digital Colleagues, Not Job Replacements: Agents work side-by-side with humans, multiplying productivity 10x to 20x.
— The Necessity of an Enterprise Intelligence Layer: Non-generic outputs require AI trained on an organization's deep context: processes, sector knowledge, regulations, and competitor data.
— Avoiding "Copy-Paste" Generic AI Outputs: Public AI prompts produce interchangeable reports; enterprise AI relies on company-specific intelligence.
— Design Processes Backwards from the North Star: Start with the desired outcome and work backward, rather than shaving off incremental steps.
— Setting Operational Guardrails: Define non-negotiables, such as budget, headcount, or compliance bounds, so AI solutions stay within constraints.
— The Token Cost as an Agent "Salary": Tokens are the salary of AI agents; deployed for growth, like sales proposals at scale, the ROI far outweighs the cost.
— Inquisitive Questioning Uncovers Real Goals: Finding the true North Star takes persistent questioning beyond "doing things faster."
— Event-Driven AI Triggering via Sensors: Emails, system logs, or IoT sensors can trigger workflows that do research and prep work proactively.
— Reverse-Engineering Enterprise Knowledge: Without documentation, organizations can use AI to research regulators, competitors, and unstructured data to bootstrap baselines.
— Rethinking Traditional Methodologies: Lean and Six Sigma must evolve because AI agents don't follow static step-by-step logic.
— Upskilling Employees Over Avoiding Tech: Change management means encouraging employees to ask better questions and learn new AI tools.
— Central Intelligence vs. Domain-Specific Needs: Legal or Finance may need specialized tools, but a unified knowledge layer prevents silos.
— Prompt & Context Engineering as Process Design: Modern BPM design relies on prompt and context engineering to guide AI agents.
— Engage with Digital Twins: Bassam highlights personal and executive digital twins (such as his own) that let stakeholders interact asynchronously with AI personas.
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